This paper presents the challenge report for the 2021 Kidney and Kidney Tumor Segmentation Challenge (KiTS21) held in conjunction with the 2021 international conference on Medical Image Computing and Computer Assisted Interventions (MICCAI). KiTS21 is a sequel to its first edition in 2019, and it features a variety of innovations in how the challenge was designed, in addition to a larger dataset. A novel annotation method was used to collect three separate annotations for each region of interest, and these annotations were performed in a fully transparent setting using a web-based annotation tool. Further, the KiTS21 test set was collected from an outside institution, challenging participants to develop methods that generalize well to new populations. Nonetheless, the top-performing teams achieved a significant improvement over the state of the art set in 2019, and this performance is shown to inch ever closer to human-level performance. An in-depth meta-analysis is presented describing which methods were used and how they faired on the leaderboard, as well as the characteristics of which cases generally saw good performance, and which did not. Overall KiTS21 facilitated a significant advancement in the state of the art in kidney tumor segmentation, and provides useful insights that are applicable to the field of semantic segmentation as a whole.

翻译：本文介绍了与2021年国际医学图像计算与计算机辅助介入会议（MICCAI）同期举办的2021年肾脏及肾脏肿瘤分割挑战赛（KiTS21）的报告。KiTS21是2019年首届赛事的延续，其在挑战设计方面引入了多项创新，并采用了更大的数据集。研究采用新型标注方法，通过基于网络的标注工具在完全透明的环境下为每个感兴趣区域收集了三组独立标注。此外，KiTS21测试集采集自外部机构，要求参赛者开发能良好泛化至新人群的方法。最终，排名前列的团队较2019年设定的技术最优水平取得了显著提升，且该性能正逐步逼近人类水平。本文进行了深入的荟萃分析，阐述了所采用的方法及其在排行榜上的表现，同时分析了通常表现良好的病例特征与表现欠佳病例的特点。总体而言，KiTS21推动了肾脏肿瘤分割技术最优水平的重大进步，并提供了适用于整个语义分割领域的宝贵见解。